Imperial College London

Emeritus ProfessorJeremyNicholson

Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Emeritus Professor of Biological Chemistry
 
 
 
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Contact

 

+44 (0)20 7594 3195j.nicholson Website

 
 
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Assistant

 

Ms Wendy Torto +44 (0)20 7594 3225

 
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Location

 

Office no. 665Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Vorkas:2015:10.1021/ac503775m,
author = {Vorkas, PA and Isaac, G and Anwar, MA and Davies, AH and Want, EJ and Nicholson, JK and Holmes, E},
doi = {10.1021/ac503775m},
journal = {Analytical Chemistry},
pages = {4184--4193},
title = {Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage: Application to Cardiovascular Disease.},
url = {http://dx.doi.org/10.1021/ac503775m},
volume = {87},
year = {2015}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Metabolic profiling studies aim to achieve broad metabolome coverage in specific biological samples. However, wide metabolome coverage has proven difficult to achieve, mostly because of the diverse physicochemical properties of small molecules, obligating analysts to seek multiplatform and multimethod approaches. Challenges are even greater when it comes to applications to tissue samples, where tissue lysis and metabolite extraction can induce significant systematic variation in composition. We have developed a pipeline for obtaining the aqueous and organic compounds from diseased arterial tissue using two consecutive extractions, followed by a different untargeted UPLC-MS analysis method for each extract. Methods were rationally chosen and optimized to address the different physicochemical properties of each extract: hydrophilic interaction liquid chromatography (HILIC) for the aqueous extract and reversed-phase chromatography for the organic. This pipeline can be generic for tissue analysis as demonstrated by applications to different tissue types. The experimental setup and fast turnaround time of the two methods contributed toward obtaining highly reproducible features with exceptional chromatographic performance (CV % < 0.5%), making this pipeline suitable for metabolic profiling applications. We structurally assigned 226 metabolites from a range of chemical classes (e.g., carnitines, α-amino acids, purines, pyrimidines, phospholipids, sphingolipids, free fatty acids, and glycerolipids) which were mapped to their corresponding pathways, biological functions and known disease mechanisms. The combination of the two untargeted UPLC-MS methods showed high metabolite complementarity. We demonstrate the application of this pipeline to cardiovascular disease, where we show that the analyzed diseased groups (n = 120) of arterial tissue could be distinguished based on their metabolic profiles.
AU - Vorkas,PA
AU - Isaac,G
AU - Anwar,MA
AU - Davies,AH
AU - Want,EJ
AU - Nicholson,JK
AU - Holmes,E
DO - 10.1021/ac503775m
EP - 4193
PY - 2015///
SN - 1086-4377
SP - 4184
TI - Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage: Application to Cardiovascular Disease.
T2 - Analytical Chemistry
UR - http://dx.doi.org/10.1021/ac503775m
UR - http://hdl.handle.net/10044/1/21292
VL - 87
ER -